Triple

T14645935
Position Surface form Disambiguated ID Type / Status
Subject Daallo Airlines E343848 entity
Predicate focusCity P164 FINISHED
Object Hargeisa E462624 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Hargeisa | Statement: [Daallo Airlines, focusCity, Hargeisa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hargeisa
Context triple: [Daallo Airlines, focusCity, Hargeisa]
  • A. Hargeisa chosen
    Hargeisa is the largest city and political, economic, and cultural center of the self-declared republic of Somaliland in the Horn of Africa.
  • B. Mogadishu
    Mogadishu is the capital and largest city of Somalia, serving as a major political, economic, and cultural center on the Horn of Africa.
  • C. Obock
    Obock is a coastal town in northeastern Djibouti, situated on the Gulf of Tadjoura and known historically as one of the country’s earliest French colonial settlements.
  • D. Banadir
    Banadir is a coastal administrative region of Somalia that includes the nation’s capital, Mogadishu, and serves as a key political and economic center.
  • E. Burao
    Burao is a key commercial and administrative city in central Somaliland, known as a major livestock trading hub in the region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4ea6d8481908e6331ca173c646b completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe64ea085c8190b308504fa11c731d completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:26 a.m.